{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\williamslaro\Documents\Research\Projects\Random Projects\Economic Voting in the States\PSRM\R&R\Replication\All Economics Is Local--Replication.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 1 May 2016, 20:44:02
{txt}
{com}. 
. *************************************************************************************
. *** National Specification
. *************************************************************************************
. ologit retnat gsp_pc2_ch gdppc_growth ch_unem inflation approve age male nonwhite union college married unemployed own_home ppid noppid

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-206003.53}  
Iteration 1:{space 3}log likelihood = {res:-164930.37}  
Iteration 2:{space 3}log likelihood = {res:-163469.79}  
Iteration 3:{space 3}log likelihood = {res:-163460.79}  
Iteration 4:{space 3}log likelihood = {res:-163460.79}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    203808
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  85085.48
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-163460.79{txt}{col 51}Pseudo R2{col 67}= {res}    0.2065

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}gsp_pc2_ch {c |}{col 14}{res}{space 2}-.0737392{col 26}{space 2} .0024312{col 37}{space 1}  -30.33{col 46}{space 3}0.000{col 54}{space 4}-.0785042{col 67}{space 3}-.0689742
{txt}gdppc_growth {c |}{col 14}{res}{space 2} .1650138{col 26}{space 2}  .007454{col 37}{space 1}   22.14{col 46}{space 3}0.000{col 54}{space 4} .1504042{col 67}{space 3} .1796234
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2} .5651257{col 26}{space 2} .0107751{col 37}{space 1}   52.45{col 46}{space 3}0.000{col 54}{space 4} .5440068{col 67}{space 3} .5862445
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} .7659062{col 26}{space 2} .0063114{col 37}{space 1}  121.35{col 46}{space 3}0.000{col 54}{space 4}  .753536{col 67}{space 3} .7782764
{txt}{space 5}approve {c |}{col 14}{res}{space 2}-1.780178{col 26}{space 2} .0141602{col 37}{space 1} -125.72{col 46}{space 3}0.000{col 54}{space 4}-1.807932{col 67}{space 3}-1.752425
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0076399{col 26}{space 2} .0003382{col 37}{space 1}   22.59{col 46}{space 3}0.000{col 54}{space 4} .0069771{col 67}{space 3} .0083027
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.3225994{col 26}{space 2} .0097737{col 37}{space 1}  -33.01{col 46}{space 3}0.000{col 54}{space 4}-.3417555{col 67}{space 3}-.3034434
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0709161{col 26}{space 2} .0117174{col 37}{space 1}    6.05{col 46}{space 3}0.000{col 54}{space 4} .0479504{col 67}{space 3} .0938817
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0734766{col 26}{space 2} .0133283{col 37}{space 1}    5.51{col 46}{space 3}0.000{col 54}{space 4} .0473537{col 67}{space 3} .0995996
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.0961851{col 26}{space 2} .0101651{col 37}{space 1}   -9.46{col 46}{space 3}0.000{col 54}{space 4}-.1161083{col 67}{space 3}-.0762619
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0353397{col 26}{space 2} .0105894{col 37}{space 1}   -3.34{col 46}{space 3}0.001{col 54}{space 4}-.0560947{col 67}{space 3}-.0145848
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .5003775{col 26}{space 2} .0191001{col 37}{space 1}   26.20{col 46}{space 3}0.000{col 54}{space 4} .4629419{col 67}{space 3} .5378131
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1831289{col 26}{space 2} .0119456{col 37}{space 1}  -15.33{col 46}{space 3}0.000{col 54}{space 4}-.2065419{col 67}{space 3} -.159716
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.5880143{col 26}{space 2} .0157779{col 37}{space 1}  -37.27{col 46}{space 3}0.000{col 54}{space 4}-.6189385{col 67}{space 3}-.5570901
{txt}{space 6}noppid {c |}{col 14}{res}{space 2} .2561015{col 26}{space 2} .0161344{col 37}{space 1}   15.87{col 46}{space 3}0.000{col 54}{space 4} .2244786{col 67}{space 3} .2877244
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2} -.612443{col 26}{space 2} .0292862{col 54}{space 4} -.669843{col 67}{space 3} -.555043
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} .7988151{col 26}{space 2} .0291711{col 54}{space 4} .7416407{col 67}{space 3} .8559895
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. *************************************************************************************
. *** NOTE: 
. *** W10: Undirected conomic mentions in media (row-standardized)
. *** W14: Economic similarity (row-standardized)
. *************************************************************************************
. 
. *************************************************************************************
. *** Table 1: Ordered logit estimates of national economic evaluations using media mentions (W10) and economic similarity (W14) W specifications
. *************************************************************************************
. foreach W in 10 14 {c -(}
{txt}  2{com}.         di _newline(2) "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  3{com}.         di "W`W'"
{txt}  4{com}.         ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch sp_W`W'_gsp_pc2_ch
{txt}  5{com}.         
.         di "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  6{com}. {c )-}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W10

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-206003.53}  
Iteration 1:{space 3}log likelihood = {res:-163735.76}  
Iteration 2:{space 3}log likelihood = {res:-162014.77}  
Iteration 3:{space 3}log likelihood = {res:-162005.65}  
Iteration 4:{space 3}log likelihood = {res:-162005.65}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    203808
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  87995.77
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-162005.65{txt}{col 51}Pseudo R2{col 67}= {res}    0.2136

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .0074797{col 26}{space 2} .0003391{col 37}{space 1}   22.06{col 46}{space 3}0.000{col 54}{space 4}  .006815{col 67}{space 3} .0081443
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.3217062{col 26}{space 2} .0097944{col 37}{space 1}  -32.85{col 46}{space 3}0.000{col 54}{space 4}-.3409029{col 67}{space 3}-.3025095
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0795138{col 26}{space 2} .0116859{col 37}{space 1}    6.80{col 46}{space 3}0.000{col 54}{space 4} .0566098{col 67}{space 3} .1024177
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0730785{col 26}{space 2} .0133557{col 37}{space 1}    5.47{col 46}{space 3}0.000{col 54}{space 4} .0469018{col 67}{space 3} .0992553
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.1007894{col 26}{space 2}  .010189{col 37}{space 1}   -9.89{col 46}{space 3}0.000{col 54}{space 4}-.1207594{col 67}{space 3}-.0808194
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0217407{col 26}{space 2} .0106047{col 37}{space 1}   -2.05{col 46}{space 3}0.040{col 54}{space 4}-.0425256{col 67}{space 3}-.0009559
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .4540028{col 26}{space 2} .0192018{col 37}{space 1}   23.64{col 46}{space 3}0.000{col 54}{space 4}  .416368{col 67}{space 3} .4916376
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1453955{col 26}{space 2} .0119629{col 37}{space 1}  -12.15{col 46}{space 3}0.000{col 54}{space 4}-.1688423{col 67}{space 3}-.1219487
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.5710517{col 26}{space 2} .0158327{col 37}{space 1}  -36.07{col 46}{space 3}0.000{col 54}{space 4}-.6020831{col 67}{space 3}-.5400202
{txt}{space 6}noppid {c |}{col 14}{res}{space 2} .2914775{col 26}{space 2} .0161622{col 37}{space 1}   18.03{col 46}{space 3}0.000{col 54}{space 4} .2598001{col 67}{space 3} .3231548
{txt}{space 5}approve {c |}{col 14}{res}{space 2}-1.826705{col 26}{space 2} .0143202{col 37}{space 1} -127.56{col 46}{space 3}0.000{col 54}{space 4}-1.854772{col 67}{space 3}-1.798638
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} .7654872{col 26}{space 2} .0060059{col 37}{space 1}  127.46{col 46}{space 3}0.000{col 54}{space 4} .7537159{col 67}{space 3} .7772585
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2}-.1239389{col 26}{space 2} .0106454{col 37}{space 1}  -11.64{col 46}{space 3}0.000{col 54}{space 4}-.1448036{col 67}{space 3}-.1030743
{txt}{space 2}gsp_pc2_ch {c |}{col 14}{res}{space 2}-.0232408{col 26}{space 2} .0024586{col 37}{space 1}   -9.45{col 46}{space 3}0.000{col 54}{space 4}-.0280595{col 67}{space 3}-.0184221
{txt}sp_W10_gsp~h {c |}{col 14}{res}{space 2}-.3778785{col 26}{space 2} .0065306{col 37}{space 1}  -57.86{col 46}{space 3}0.000{col 54}{space 4}-.3906784{col 67}{space 3}-.3650787
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.731087{col 26}{space 2} .0316455{col 54}{space 4}-1.793111{col 67}{space 3}-1.669063
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-.2953527{col 26}{space 2} .0312218{col 54}{space 4}-.3565464{col 67}{space 3} -.234159
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W14

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-206003.53}  
Iteration 1:{space 3}log likelihood = {res: -164223.7}  
Iteration 2:{space 3}log likelihood = {res:-162546.49}  
Iteration 3:{space 3}log likelihood = {res:-162537.31}  
Iteration 4:{space 3}log likelihood = {res:-162537.31}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    203808
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  86932.44
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-162537.31{txt}{col 51}Pseudo R2{col 67}= {res}    0.2110

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .0075717{col 26}{space 2} .0003386{col 37}{space 1}   22.36{col 46}{space 3}0.000{col 54}{space 4}  .006908{col 67}{space 3} .0082353
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.3228689{col 26}{space 2}  .009781{col 37}{space 1}  -33.01{col 46}{space 3}0.000{col 54}{space 4}-.3420393{col 67}{space 3}-.3036985
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0898584{col 26}{space 2}  .011681{col 37}{space 1}    7.69{col 46}{space 3}0.000{col 54}{space 4} .0669641{col 67}{space 3} .1127528
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0626513{col 26}{space 2} .0133427{col 37}{space 1}    4.70{col 46}{space 3}0.000{col 54}{space 4}    .0365{col 67}{space 3} .0888026
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.0891273{col 26}{space 2}  .010172{col 37}{space 1}   -8.76{col 46}{space 3}0.000{col 54}{space 4}-.1090641{col 67}{space 3}-.0691906
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0199074{col 26}{space 2}  .010592{col 37}{space 1}   -1.88{col 46}{space 3}0.060{col 54}{space 4}-.0406674{col 67}{space 3} .0008526
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .4603271{col 26}{space 2} .0191581{col 37}{space 1}   24.03{col 46}{space 3}0.000{col 54}{space 4} .4227779{col 67}{space 3} .4978764
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1420765{col 26}{space 2} .0119547{col 37}{space 1}  -11.88{col 46}{space 3}0.000{col 54}{space 4}-.1655072{col 67}{space 3}-.1186457
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.5675852{col 26}{space 2} .0158038{col 37}{space 1}  -35.91{col 46}{space 3}0.000{col 54}{space 4}  -.59856{col 67}{space 3}-.5366103
{txt}{space 6}noppid {c |}{col 14}{res}{space 2}  .293975{col 26}{space 2} .0161479{col 37}{space 1}   18.21{col 46}{space 3}0.000{col 54}{space 4} .2623257{col 67}{space 3} .3256243
{txt}{space 5}approve {c |}{col 14}{res}{space 2}-1.820593{col 26}{space 2} .0142915{col 37}{space 1} -127.39{col 46}{space 3}0.000{col 54}{space 4}-1.848603{col 67}{space 3}-1.792582
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} .7513537{col 26}{space 2}  .005968{col 37}{space 1}  125.90{col 46}{space 3}0.000{col 54}{space 4} .7396566{col 67}{space 3} .7630508
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2}-.0839881{col 26}{space 2} .0113794{col 37}{space 1}   -7.38{col 46}{space 3}0.000{col 54}{space 4}-.1062914{col 67}{space 3}-.0616849
{txt}{space 2}gsp_pc2_ch {c |}{col 14}{res}{space 2}-.0181138{col 26}{space 2} .0025301{col 37}{space 1}   -7.16{col 46}{space 3}0.000{col 54}{space 4}-.0230726{col 67}{space 3}-.0131549
{txt}sp_W14_gsp~h {c |}{col 14}{res}{space 2}-.3849997{col 26}{space 2} .0079872{col 37}{space 1}  -48.20{col 46}{space 3}0.000{col 54}{space 4}-.4006543{col 67}{space 3} -.369345
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.797716{col 26}{space 2} .0340176{col 54}{space 4}-1.864389{col 67}{space 3}-1.731043
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-.3696964{col 26}{space 2} .0336024{col 54}{space 4}-.4355559{col 67}{space 3}-.3038369
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

{com}. 
. 
. *************************************************************************************
. *** Table 2: Substantive effects of the explanatory variables on the predicted probaiblity of evaluating the national economy as having gotten "worse" over the last 12 months
. *************************************************************************************
. use `data', clear
{txt}
{com}. 
. tempname wm
{txt}
{com}. tempfile wresults
{txt}
{com}. postfile `wm' model outcome str20 w str20 v d lo hi /*
> */      epcp worse_class model_class naive_class aic bic auc auc_lo auc_hi using `wresults', replace
{txt}(note: file C:\Users\WILLIA~1\AppData\Local\Temp\ST_0100000n.tmp not found)

{com}. 
. foreach W in W10 W14 {c -(}
{txt}  2{com}.         di _newline(3)
{txt}  3{com}.         nois display "**************************************"
{txt}  4{com}. 
.         nois display "Weights matrix = `W'"
{txt}  5{com}. 
.         tempvar pr1_1 pr2_1 pr3_1 g_pr1_2 g_pr2_2 g_pr3_2 gsp_pr1_2 gsp_pr2_2 gsp_pr3_2 dg_pr1 dg_pr2 dg_pr3 dgsp_pr1 dgsp_pr2 dgsp_pr3
{txt}  6{com}. 
.         qui ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch sp_`W'_gsp_pc2_ch
{txt}  7{com}.         fit, auc
{txt}  8{com}. 
.         local epcp = r(ePCP)
{txt}  9{com}.         local worse_class = r(worse_class)
{txt} 10{com}.         local model_class = r(model_class)
{txt} 11{com}.         local naive_class = r(naive_class)
{txt} 12{com}.         local aic = r(aic)
{txt} 13{com}.         local bic = r(bic)
{txt} 14{com}.                 
.         local auc = r(auc)
{txt} 15{com}.         local auc_lo = r(auc_lo)
{txt} 16{com}.         local auc_hi = r(auc_hi)        
{txt} 17{com}.         
.         set seed 648
{txt} 18{com}.         qui estsimp ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch sp_`W'_gsp_pc2_ch, genname(ggg)  
{txt} 19{com}. 
.         setx (age) mean (inflation ch_unem) p25 (male nonwhite union college married unemployed own_home) p50 (ppid noppid) min (approve) max
{txt} 20{com}.         simqi, prval(1 2 3)
{txt} 21{com}. 
.         setx gsp_pc2_ch 3 sp_`W'_gsp_pc2_ch 3
{txt} 22{com}.         simqi, prval(1 2 3) genpr(`pr1_1' `pr2_1' `pr3_1')
{txt} 23{com}.         
.         setx gsp_pc2_ch 1 sp_`W'_gsp_pc2_ch 3
{txt} 24{com}.         simqi, prval(1 2 3) genpr(`g_pr1_2' `g_pr2_2' `g_pr3_2')
{txt} 25{com}.         
.         setx gsp_pc2_ch 3 sp_`W'_gsp_pc2_ch 1
{txt} 26{com}.         simqi, prval(1 2 3) genpr(`gsp_pr1_2' `gsp_pr2_2' `gsp_pr3_2')
{txt} 27{com}.         
.         *** GSP per capita
.         gen `dg_pr1' = `g_pr1_2' - `pr1_1'
{txt} 28{com}.         qui sum `dg_pr1'
{txt} 29{com}.         local mn_p_1 = round(r(mean), 0.001)
{txt} 30{com}.         qui _pctile `dg_pr1', perc(2.5 97.5)
{txt} 31{com}.         local lo_p_1 = round(r(r1), 0.001)
{txt} 32{com}.         local hi_p_1 = round(r(r2), 0.001)
{txt} 33{com}. 
.         gen `dg_pr2' = `g_pr2_2' - `pr2_1'
{txt} 34{com}.         qui sum `dg_pr2'
{txt} 35{com}.         local mn_p_2 = round(r(mean), 0.001)
{txt} 36{com}.         qui _pctile `dg_pr2', perc(2.5 97.5)
{txt} 37{com}.         local lo_p_2 = round(r(r1), 0.001)
{txt} 38{com}.         local hi_p_2 = round(r(r2), 0.001)
{txt} 39{com}. 
.         gen `dg_pr3' = `g_pr3_2' - `pr3_1'
{txt} 40{com}.         qui sum `dg_pr3'
{txt} 41{com}.         local mn_p_3 = round(r(mean), 0.001)
{txt} 42{com}.         qui _pctile `dg_pr3', perc(2.5 97.5)
{txt} 43{com}.         local lo_p_3 = round(r(r1), 0.001)
{txt} 44{com}.         local hi_p_3 = round(r(r2), 0.001)
{txt} 45{com}. 
.         foreach n of numlist 1(1)3 {c -(}
{txt} 46{com}.                 if `n' == 1 {c -(} 
{txt} 47{com}.                         post `wm' (1) (`n') ("`W'") ("GSP") (`mn_p_`n'') (`lo_p_`n'') (`hi_p_`n'') (`epcp') (`worse_class') (`model_class') (`naive_class') (`aic') (`bic') (`auc') (`auc_lo') (`auc_hi') 
{txt} 48{com}.                 {c )-}
{txt} 49{com}.                 else {c -(}
{txt} 50{com}.                         post `wm' (1) (`n') ("`W'") ("GSP") (`mn_p_`n'') (`lo_p_`n'') (`hi_p_`n'') (.) (.) (.) (.) (.) (.) (.) (.) (.)
{txt} 51{com}.                 {c )-}
{txt} 52{com}.         {c )-}       
{txt} 53{com}.         
.         *** GSP per capita: spatial lag
.         gen `dgsp_pr1' = `gsp_pr1_2' - `pr1_1'
{txt} 54{com}.         qui sum `dgsp_pr1'
{txt} 55{com}.         local mn_p_1 = round(r(mean), 0.001)
{txt} 56{com}.         qui _pctile `dgsp_pr1', perc(2.5 97.5)
{txt} 57{com}.         local lo_p_1 = round(r(r1), 0.001)
{txt} 58{com}.         local hi_p_1 = round(r(r2), 0.001)
{txt} 59{com}. 
.         gen `dgsp_pr2' = `gsp_pr2_2' - `pr2_1'
{txt} 60{com}.         qui sum `dgsp_pr2'
{txt} 61{com}.         local mn_p_2 = round(r(mean), 0.001)
{txt} 62{com}.         qui _pctile `dgsp_pr2', perc(2.5 97.5)
{txt} 63{com}.         local lo_p_2 = round(r(r1), 0.001)
{txt} 64{com}.         local hi_p_2 = round(r(r2), 0.001)
{txt} 65{com}. 
.         gen `dgsp_pr3' = `gsp_pr3_2' - `pr3_1'
{txt} 66{com}.         qui sum `dgsp_pr3'
{txt} 67{com}.         local mn_p_3 = round(r(mean), 0.001)
{txt} 68{com}.         qui _pctile `dgsp_pr3', perc(2.5 97.5)
{txt} 69{com}.         local lo_p_3 = round(r(r1), 0.001)
{txt} 70{com}.         local hi_p_3 = round(r(r2), 0.001)
{txt} 71{com}.         
.         foreach n of numlist 1(1)3 {c -(}
{txt} 72{com}.                 post `wm' (1) (`n') ("`W'") ("GSP SL") (`mn_p_`n'') (`lo_p_`n'') (`hi_p_`n'') (.) (.) (.) (.) (.) (.) (.) (.) (.)  
{txt} 73{com}.         {c )-}       
{txt} 74{com}. 
.         drop ggg*
{txt} 75{com}.         nois display _newline(3) "**************************************"
{txt} 76{com}. {c )-}




**************************************
Weights matrix = W10

{res}-> tabulation of __00000O by retnat  
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

           {c |}    Retrospective evaluations
           {c |}     [economy_retrospective]
  __00000O {c |}    Better  Stay the       Worse {c |}     Total
{hline 11}{c +}{hline 33}{c +}{hline 10}
         1 {c |}{res}    38,536     19,818     10,682 {txt}{c |}{res}    69,036 
           {txt}{c |}{res}     76.87      44.73       9.77 {txt}{c |}{res}     33.87 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
         2 {c |}{res}       894        965        728 {txt}{c |}{res}     2,587 
           {txt}{c |}{res}      1.78       2.18       0.67 {txt}{c |}{res}      1.27 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
         3 {c |}{res}    10,704     23,524     97,957 {txt}{c |}{res}   132,185 
           {txt}{c |}{res}     21.35      53.09      89.57 {txt}{c |}{res}     64.86 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
     Total {c |}{res}    50,134     44,307    109,367 {txt}{c |}{res}   203,808 
           {txt}{c |}{res}    100.00     100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}4{txt}) = {res} 7.4e+04  {txt} Pr = {res}0.000



AIC = 324045.29
BIC = 324219.12
Naive classification = 53.7
Model classification = 67.4
ePCP = 53.8
% of worse correctly classified = 89.6
Area under the curve (AUC) = .821  95% CI = [.819, .823]

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .1869731     .0049856      .176946      .19708
       {txt}Pr(retnat=Stay the) |  {res}  .304431     .0033485       .29769    .3110026
          {txt}Pr(retnat=Worse) |  {res} .5085959     .0080975     .4929216    .5247965

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .4334932     .0049351      .423478    .4432464
       {txt}Pr(retnat=Stay the) |  {res} .3292888     .0018533     .3256539    .3327677
          {txt}Pr(retnat=Worse) |  {res}  .237218      .003654     .2301591    .2444924

Simqi generated the following new variable(s): __000001 __000002 __000003

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .4221519     .0051641     .4118469    .4324245
       {txt}Pr(retnat=Stay the) |  {res} .3321419     .0018353     .3286292    .3356685
          {txt}Pr(retnat=Worse) |  {res} .2457062     .0039218     .2378884    .2537003

Simqi generated the following new variable(s): __000004 __000005 __000006

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .2644848     .0053193     .2538715    .2750637
       {txt}Pr(retnat=Stay the) |  {res} .3372507     .0018113      .333645    .3408848
          {txt}Pr(retnat=Worse) |  {res} .3982645      .006502     .3856291    .4112352

Simqi generated the following new variable(s): __000007 __000008 __000009
{txt}(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)



**************************************




**************************************
Weights matrix = W14

{res}-> tabulation of __000013 by retnat  
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

           {c |}    Retrospective evaluations
           {c |}     [economy_retrospective]
  __000013 {c |}    Better  Stay the       Worse {c |}     Total
{hline 11}{c +}{hline 33}{c +}{hline 10}
         1 {c |}{res}    38,852     20,233     10,961 {txt}{c |}{res}    70,046 
           {txt}{c |}{res}     77.50      45.67      10.02 {txt}{c |}{res}     34.37 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
         2 {c |}{res}       765        891        650 {txt}{c |}{res}     2,306 
           {txt}{c |}{res}      1.53       2.01       0.59 {txt}{c |}{res}      1.13 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
         3 {c |}{res}    10,517     23,183     97,756 {txt}{c |}{res}   131,456 
           {txt}{c |}{res}     20.98      52.32      89.38 {txt}{c |}{res}     64.50 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
     Total {c |}{res}    50,134     44,307    109,367 {txt}{c |}{res}   203,808 
           {txt}{c |}{res}    100.00     100.00     100.00 {txt}{c |}{res}    100.00 

{txt}          Pearson chi2({res}4{txt}) = {res} 7.5e+04  {txt} Pr = {res}0.000



AIC = 325108.61
BIC = 325282.44
Naive classification = 53.7
Model classification = 67.5
ePCP = 53.7
% of worse correctly classified = 89.4
Area under the curve (AUC) = .818  95% CI = [.816, .82]

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .1828944     .0055194     .1719367    .1936401
       {txt}Pr(retnat=Stay the) |  {res} .2998021     .0038117     .2920774    .3072134
          {txt}Pr(retnat=Worse) |  {res} .5173035     .0091305     .4998047    .5355988

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .4282522     .0050576     .4181492    .4384066
       {txt}Pr(retnat=Stay the) |  {res} .3292254     .0018312     .3256273    .3326815
          {txt}Pr(retnat=Worse) |  {res} .2425224     .0038089     .2350747    .2500715

Simqi generated the following new variable(s): __00000G __00000H __00000I

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .4194338     .0052265     .4089486    .4298543
       {txt}Pr(retnat=Stay the) |  {res} .3313462     .0018138      .327877    .3348495
          {txt}Pr(retnat=Worse) |  {res} .2492201     .0040131     .2413469    .2573815

Simqi generated the following new variable(s): __00000J __00000K __00000L

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .2576565     .0058842     .2457725    .2693965
       {txt}Pr(retnat=Stay the) |  {res} .3336883     .0020238     .3295733    .3376801
          {txt}Pr(retnat=Worse) |  {res} .4086552     .0073837     .3943685    .4236074

Simqi generated the following new variable(s): __00000M __00000N __00000O
{txt}(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)
(212106 missing values generated)



**************************************

{com}. 
. postclose `wm'
{txt}
{com}. 
. 
. use `wresults', clear
{txt}
{com}. 
. gen w2 = w
{txt}
{com}. replace w2 = "Media Mentions" if w2 == "W10"
{txt}w2 was {res}str3{txt} now {res}str14
{txt}(6 real changes made)

{com}. replace w2 = "Economic Similarity" if w2 == "W14"
{txt}w2 was {res}str14{txt} now {res}str19
{txt}(6 real changes made)

{com}. 
. save "wmodels.dta", replace 
{txt}file wmodels.dta saved

{com}. 
. *** Substantive effects of the control variables
. use `data', clear
{txt}
{com}. 
. foreach W in W10 W14 {c -(}
{txt}  2{com}.         di _newline(3)
{txt}  3{com}.         nois display "**************************************"
{txt}  4{com}.         nois display "Weights matrix = `W'"
{txt}  5{com}. 
.         set seed 648
{txt}  6{com}.         qui estsimp ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch sp_`W'_gsp_pc2_ch, genname(ggg)  
{txt}  7{com}. 
.         setx (age) mean (inflation ch_unem) p25 (male nonwhite union college married unemployed own_home) p50 (ppid noppid) min (approve) max
{txt}  8{com}.         simqi, prval(1 2 3)
{txt}  9{com}.         
.         simqi, fd(prval(1 2 3)) changex(gsp_pc2_ch 3 1)
{txt} 10{com}.         simqi, fd(prval(1 2 3)) changex(sp_`W'_gsp_pc2_ch 3 1)
{txt} 11{com}.         simqi, fd(prval(1 2 3)) changex(age 51 67)
{txt} 12{com}.         simqi, fd(prval(1 2 3)) changex(male 0 1)
{txt} 13{com}.         simqi, fd(prval(1 2 3)) changex(nonwhite 0 1)
{txt} 14{com}.         simqi, fd(prval(1 2 3)) changex(union 0 1)
{txt} 15{com}.         simqi, fd(prval(1 2 3)) changex(college 0 1)
{txt} 16{com}.         simqi, fd(prval(1 2 3)) changex(married 0 1)
{txt} 17{com}.         simqi, fd(prval(1 2 3)) changex(unemployed 0 1) 
{txt} 18{com}.         simqi, fd(prval(1 2 3)) changex(own_home 0 1)
{txt} 19{com}.         simqi, fd(prval(1 2 3)) changex(ppid 0 1)
{txt} 20{com}.         simqi, fd(prval(1 2 3)) changex(noppid 0 1)
{txt} 21{com}.         simqi, fd(prval(1 2 3)) changex(approve 0 1)
{txt} 22{com}.         simqi, fd(prval(1 2 3)) changex(inflation 2.4 3.5)
{txt} 23{com}.         simqi, fd(prval(1 2 3)) changex(ch_unem 0 1)
{txt} 24{com}. 
.         drop ggg*
{txt} 25{com}.         nois display _newline(3) "**************************************"
{txt} 26{com}. {c )-}




**************************************
Weights matrix = W10

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .1869731     .0049856      .176946      .19708
       {txt}Pr(retnat=Stay the) |  {res}  .304431     .0033485       .29769    .3110026
          {txt}Pr(retnat=Worse) |  {res} .5085959     .0080975     .4929216    .5247965

First Difference: gsp_pc2_ch 3 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0072479     .0007749    -.0087435   -.0057068
           {txt}dPr(retnat = 2) |  {res}-.0043333     .0004826    -.0053208   -.0033616
           {txt}dPr(retnat = 3) |  {res} .0115813     .0012213     .0090798    .0140104

First Difference: sp_W10_gsp_pc2_ch 3 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.1653219     .0024923    -.1702916    -.160437
           {txt}dPr(retnat = 2) |  {res} .0003165     .0026571    -.0048704    .0053834
           {txt}dPr(retnat = 3) |  {res} .1650053     .0036388     .1576842    .1725765

First Difference: age 51 67

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0175085     .0008587     -.019224   -.0157937
           {txt}dPr(retnat = 2) |  {res}-.0123323     .0006592    -.0135792   -.0109897
           {txt}dPr(retnat = 3) |  {res} .0298408      .001351     .0272039    .0323969

First Difference: male 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0538732     .0019444      .050112    .0578799
           {txt}dPr(retnat = 2) |  {res} .0260665     .0013824     .0232889    .0286922
           {txt}dPr(retnat = 3) |  {res}-.0799397     .0024207    -.0847414   -.0750624

First Difference: nonwhite 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} -.011801     .0017454    -.0151679   -.0082825
           {txt}dPr(retnat = 2) |  {res}-.0080693     .0012059    -.0103827   -.0057753
           {txt}dPr(retnat = 3) |  {res} .0198703     .0029139     .0141824    .0252917

First Difference: union 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0108131     .0019581    -.0148219   -.0068523
           {txt}dPr(retnat = 2) |  {res}-.0073679     .0013979     -.010064   -.0045919
           {txt}dPr(retnat = 3) |  {res}  .018181     .0033271     .0115303    .0245739

First Difference: college 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}  .015768     .0016973     .0124125    .0191676
           {txt}dPr(retnat = 2) |  {res} .0093597     .0010382     .0073297    .0115254
           {txt}dPr(retnat = 3) |  {res}-.0251277     .0026552     -.030328   -.0197753

First Difference: married 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0034457     .0016201     .0002549    .0066704
           {txt}dPr(retnat = 2) |  {res} .0022597      .001068     .0001669    .0043929
           {txt}dPr(retnat = 3) |  {res}-.0057054     .0026836    -.0110779   -.0004218

First Difference: unemployed 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0595572     .0025444    -.0640908    -.054087
           {txt}dPr(retnat = 2) |  {res}-.0516263     .0024735     -.056261   -.0466119
           {txt}dPr(retnat = 3) |  {res} .1111834     .0044962     .1017012    .1194392

First Difference: own_home 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}  .021123     .0017559     .0175977    .0243458
           {txt}dPr(retnat = 2) |  {res} .0151375     .0013046     .0125859    .0176985
           {txt}dPr(retnat = 3) |  {res}-.0362605     .0029459    -.0418178   -.0304365

First Difference: ppid 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .1022178     .0030252     .0965195    .1081278
           {txt}dPr(retnat = 2) |  {res} .0372867     .0025105     .0323162    .0424016
           {txt}dPr(retnat = 3) |  {res}-.1395045     .0039762     -.147597   -.1316927

First Difference: noppid 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0403852     .0023956    -.0452863     -.03601
           {txt}dPr(retnat = 2) |  {res}-.0318453     .0018388    -.0355391   -.0283755
           {txt}dPr(retnat = 3) |  {res} .0722305     .0039614     .0648531    .0800288

First Difference: approve 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .1512789     .0039612       .14328    .1590965
           {txt}dPr(retnat = 2) |  {res} .2055169       .00166     .2022311    .2089559
           {txt}dPr(retnat = 3) |  {res}-.3567958      .004915    -.3662556     -.34708

First Difference: inflation 2.4 3.5

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0614293      .001681     -.064799   -.0580357
           {txt}dPr(retnat = 2) |  {res}-.1005055     .0010603    -.1027175    -.098523
           {txt}dPr(retnat = 3) |  {res} .1619349     .0025245     .1568189    .1668652

First Difference: ch_unem 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0205943     .0016971     .0172691    .0240165
           {txt}dPr(retnat = 2) |  {res} .0100602     .0010863     .0079589    .0122543
           {txt}dPr(retnat = 3) |  {res}-.0306544     .0027328    -.0362522   -.0252455



**************************************




**************************************
Weights matrix = W14

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
         Pr(retnat=Better) |  {res} .1828944     .0055194     .1719367    .1936401
       {txt}Pr(retnat=Stay the) |  {res} .2998021     .0038117     .2920774    .3072134
          {txt}Pr(retnat=Worse) |  {res} .5173035     .0091305     .4998047    .5355988

First Difference: gsp_pc2_ch 3 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0055223     .0007872    -.0070531   -.0039445
           {txt}dPr(retnat = 2) |  {res}-.0035017     .0004896    -.0044714   -.0024983
           {txt}dPr(retnat = 3) |  {res} .0090241     .0012506     .0064156    .0115159

First Difference: sp_W14_gsp_pc2_ch 3 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.1676115     .0029189    -.1734423   -.1618724
           {txt}dPr(retnat = 2) |  {res}-.0015793     .0028444    -.0072027    .0038213
           {txt}dPr(retnat = 3) |  {res} .1691908     .0043832     .1602627    .1781682

First Difference: age 51 67

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0174068     .0008654    -.0191214   -.0156945
           {txt}dPr(retnat = 2) |  {res}-.0127383     .0006815    -.0140447   -.0113384
           {txt}dPr(retnat = 3) |  {res} .0301451     .0013464     .0275139    .0327039

First Difference: male 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0532461     .0019944      .049395    .0573694
           {txt}dPr(retnat = 2) |  {res} .0271248     .0014869     .0241237    .0299222
           {txt}dPr(retnat = 3) |  {res}-.0803709     .0024213    -.0851857   -.0754613

First Difference: nonwhite 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0130602      .001717    -.0163529   -.0096053
           {txt}dPr(retnat = 2) |  {res} -.009347     .0012454    -.0117624   -.0069302
           {txt}dPr(retnat = 3) |  {res} .0224072     .0029064     .0167309    .0278138

First Difference: union 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0091355     .0019351    -.0130861   -.0052473
           {txt}dPr(retnat = 2) |  {res}-.0064224     .0014097    -.0091477   -.0036002
           {txt}dPr(retnat = 3) |  {res} .0155579     .0033191     .0089222    .0219505

First Difference: college 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0136598     .0016634     .0103706    .0169816
           {txt}dPr(retnat = 2) |  {res} .0085514     .0010615     .0064573    .0107677
           {txt}dPr(retnat = 3) |  {res}-.0222112     .0026509    -.0274144   -.0168668

First Difference: married 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0031169     .0015924    -.0000179    .0062894
           {txt}dPr(retnat = 2) |  {res} .0021243     .0010895    -.0000112    .0043011
           {txt}dPr(retnat = 3) |  {res}-.0052412     .0026773    -.0106009    .0000292

First Difference: unemployed 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0591424     .0025976    -.0639182   -.0536526
           {txt}dPr(retnat = 2) |  {res}  -.05298     .0024899     -.057649   -.0479213
           {txt}dPr(retnat = 3) |  {res} .1121224     .0044634     .1027316    .1203653

First Difference: own_home 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}  .020303     .0017486     .0167682    .0235327
           {txt}dPr(retnat = 2) |  {res} .0150569     .0013207     .0124978    .0176456
           {txt}dPr(retnat = 3) |  {res}-.0353599     .0029397    -.0409077   -.0295355

First Difference: ppid 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}  .100057     .0031271     .0942212    .1059993
           {txt}dPr(retnat = 2) |  {res} .0391782      .002726      .033795    .0446382
           {txt}dPr(retnat = 3) |  {res}-.1392352     .0039705    -.1473794   -.1313864

First Difference: noppid 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0399642      .002396     -.044939   -.0356321
           {txt}dPr(retnat = 2) |  {res}-.0326192     .0018814    -.0363538   -.0290645
           {txt}dPr(retnat = 3) |  {res} .0725834     .0039469     .0653108    .0803563

First Difference: approve 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .1479128     .0043595     .1392607    .1565736
           {txt}dPr(retnat = 2) |  {res} .2034773     .0017236     .2000023    .2067689
           {txt}dPr(retnat = 3) |  {res}-.3513901     .0054579    -.3616861   -.3404141

First Difference: inflation 2.4 3.5

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res}-.0598314     .0018465    -.0634967   -.0561898
           {txt}dPr(retnat = 2) |  {res}-.0979372     .0011274    -.1002415   -.0957321
           {txt}dPr(retnat = 3) |  {res} .1577685     .0027849     .1521202    .1631469

First Difference: ch_unem 0 1

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
           dPr(retnat = 1) |  {res} .0132616     .0017397     .0098074    .0167066
           {txt}dPr(retnat = 2) |  {res} .0075095     .0011912     .0051677    .0099332
           {txt}dPr(retnat = 3) |  {res}-.0207711     .0029104    -.0266795   -.0150158



**************************************
{txt}
{com}. 
. *************************************************************************************
. *************************************************************************************
. *** Robustness Checks
. *************************************************************************************
. *************************************************************************************
. 
. *************************************************************************************
. *** Table 1: Ordered logit estimates of national economic evaluations using media mentions (W10) and economic similarity (W14) W specifications: Excluding 2009 and 2010
. *************************************************************************************
. foreach W in 10 14 {c -(}
{txt}  2{com}.         di _newline(2) "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  3{com}.         di "W`W'"
{txt}  4{com}.         ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch sp_W`W'_gsp_pc2_ch if inlist(year, 2006, 2008, 2011, 2012)
{txt}  5{com}.         estat ic
{txt}  6{com}.         
.         di "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  7{com}. {c )-}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W10

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-135692.53}  
Iteration 1:{space 3}log likelihood = {res: -93587.82}  
Iteration 2:{space 3}log likelihood = {res:-88958.377}  
Iteration 3:{space 3}log likelihood = {res:-88876.005}  
Iteration 4:{space 3}log likelihood = {res:-88875.952}  
Iteration 5:{space 3}log likelihood = {res:-88875.952}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    137556
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  93633.15
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-88875.952{txt}{col 51}Pseudo R2{col 67}= {res}    0.3450

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2}  .006196{col 26}{space 2} .0004468{col 37}{space 1}   13.87{col 46}{space 3}0.000{col 54}{space 4} .0053202{col 67}{space 3} .0070717
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.4249751{col 26}{space 2}  .013104{col 37}{space 1}  -32.43{col 46}{space 3}0.000{col 54}{space 4}-.4506585{col 67}{space 3}-.3992916
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0785676{col 26}{space 2} .0155403{col 37}{space 1}    5.06{col 46}{space 3}0.000{col 54}{space 4} .0481091{col 67}{space 3} .1090261
{txt}{space 7}union {c |}{col 14}{res}{space 2}  .055738{col 26}{space 2} .0179511{col 37}{space 1}    3.10{col 46}{space 3}0.002{col 54}{space 4} .0205546{col 67}{space 3} .0909215
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.3287589{col 26}{space 2} .0139493{col 37}{space 1}  -23.57{col 46}{space 3}0.000{col 54}{space 4}-.3560989{col 67}{space 3}-.3014189
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0148754{col 26}{space 2} .0141605{col 37}{space 1}   -1.05{col 46}{space 3}0.293{col 54}{space 4}-.0426296{col 67}{space 3} .0128787
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .5509757{col 26}{space 2} .0266167{col 37}{space 1}   20.70{col 46}{space 3}0.000{col 54}{space 4} .4988079{col 67}{space 3} .6031435
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1227375{col 26}{space 2} .0159041{col 37}{space 1}   -7.72{col 46}{space 3}0.000{col 54}{space 4}-.1539089{col 67}{space 3}-.0915661
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.8530153{col 26}{space 2} .0209162{col 37}{space 1}  -40.78{col 46}{space 3}0.000{col 54}{space 4}-.8940102{col 67}{space 3}-.8120203
{txt}{space 6}noppid {c |}{col 14}{res}{space 2} .3527963{col 26}{space 2} .0213726{col 37}{space 1}   16.51{col 46}{space 3}0.000{col 54}{space 4} .3109067{col 67}{space 3} .3946859
{txt}{space 5}approve {c |}{col 14}{res}{space 2}-2.436874{col 26}{space 2}  .019576{col 37}{space 1} -124.48{col 46}{space 3}0.000{col 54}{space 4}-2.475243{col 67}{space 3}-2.398506
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} .1633323{col 26}{space 2}  .015615{col 37}{space 1}   10.46{col 46}{space 3}0.000{col 54}{space 4} .1327274{col 67}{space 3} .1939371
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2} .7325467{col 26}{space 2} .0233516{col 37}{space 1}   31.37{col 46}{space 3}0.000{col 54}{space 4} .6867784{col 67}{space 3}  .778315
{txt}{space 2}gsp_pc2_ch {c |}{col 14}{res}{space 2}-.0551322{col 26}{space 2} .0035551{col 37}{space 1}  -15.51{col 46}{space 3}0.000{col 54}{space 4}   -.0621{col 67}{space 3}-.0481643
{txt}sp_W10_gsp~h {c |}{col 14}{res}{space 2}-.6389743{col 26}{space 2} .0087034{col 37}{space 1}  -73.42{col 46}{space 3}0.000{col 54}{space 4}-.6560326{col 67}{space 3} -.621916
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-5.516757{col 26}{space 2} .0584836{col 54}{space 4}-5.631383{col 67}{space 3}-5.402132
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-3.757537{col 26}{space 2} .0569265{col 54}{space 4}-3.869111{col 67}{space 3}-3.645963
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17}137556{col 25}-135692.5{col 37}-88875.95{col 48}   17{col 57} 177785.9{col 69}   177953
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W14

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-135692.53}  
Iteration 1:{space 3}log likelihood = {res:  -93166.4}  
Iteration 2:{space 3}log likelihood = {res:-88400.752}  
Iteration 3:{space 3}log likelihood = {res:-88314.935}  
Iteration 4:{space 3}log likelihood = {res:-88314.871}  
Iteration 5:{space 3}log likelihood = {res:-88314.871}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    137556
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  94755.32
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-88314.871{txt}{col 51}Pseudo R2{col 67}= {res}    0.3492

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2}  .005594{col 26}{space 2} .0004482{col 37}{space 1}   12.48{col 46}{space 3}0.000{col 54}{space 4} .0047155{col 67}{space 3} .0064726
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.4330689{col 26}{space 2} .0131445{col 37}{space 1}  -32.95{col 46}{space 3}0.000{col 54}{space 4}-.4588316{col 67}{space 3}-.4073062
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0910893{col 26}{space 2} .0155491{col 37}{space 1}    5.86{col 46}{space 3}0.000{col 54}{space 4} .0606135{col 67}{space 3}  .121565
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0315279{col 26}{space 2} .0179817{col 37}{space 1}    1.75{col 46}{space 3}0.080{col 54}{space 4}-.0037156{col 67}{space 3} .0667714
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.3458569{col 26}{space 2}  .013993{col 37}{space 1}  -24.72{col 46}{space 3}0.000{col 54}{space 4}-.3732827{col 67}{space 3}-.3184311
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0073167{col 26}{space 2} .0141914{col 37}{space 1}   -0.52{col 46}{space 3}0.606{col 54}{space 4}-.0351314{col 67}{space 3}  .020498
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2}  .529391{col 26}{space 2} .0266254{col 37}{space 1}   19.88{col 46}{space 3}0.000{col 54}{space 4} .4772061{col 67}{space 3} .5815759
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.0941439{col 26}{space 2} .0159408{col 37}{space 1}   -5.91{col 46}{space 3}0.000{col 54}{space 4}-.1253872{col 67}{space 3}-.0629006
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.8580833{col 26}{space 2} .0209846{col 37}{space 1}  -40.89{col 46}{space 3}0.000{col 54}{space 4}-.8992123{col 67}{space 3}-.8169543
{txt}{space 6}noppid {c |}{col 14}{res}{space 2}  .373744{col 26}{space 2} .0214319{col 37}{space 1}   17.44{col 46}{space 3}0.000{col 54}{space 4} .3317383{col 67}{space 3} .4157496
{txt}{space 5}approve {c |}{col 14}{res}{space 2} -2.45675{col 26}{space 2} .0197025{col 37}{space 1} -124.69{col 46}{space 3}0.000{col 54}{space 4}-2.495366{col 67}{space 3}-2.418134
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} .4851159{col 26}{space 2} .0174431{col 37}{space 1}   27.81{col 46}{space 3}0.000{col 54}{space 4} .4509281{col 67}{space 3} .5193037
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2} .1536261{col 26}{space 2} .0276465{col 37}{space 1}    5.56{col 46}{space 3}0.000{col 54}{space 4} .0994399{col 67}{space 3} .2078123
{txt}{space 2}gsp_pc2_ch {c |}{col 14}{res}{space 2}-.0133405{col 26}{space 2}  .003718{col 37}{space 1}   -3.59{col 46}{space 3}0.000{col 54}{space 4}-.0206278{col 67}{space 3}-.0060533
{txt}sp_W14_gsp~h {c |}{col 14}{res}{space 2}-1.007032{col 26}{space 2} .0125805{col 37}{space 1}  -80.05{col 46}{space 3}0.000{col 54}{space 4}-1.031689{col 67}{space 3}-.9823749
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2} -5.57339{col 26}{space 2} .0587089{col 54}{space 4}-5.688457{col 67}{space 3}-5.458322
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-3.797467{col 26}{space 2} .0571494{col 54}{space 4}-3.909478{col 67}{space 3}-3.685457
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17}137556{col 25}-135692.5{col 37}-88314.87{col 48}   17{col 57} 176663.7{col 69} 176830.9
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

{com}. 
. 
. *************************************************************************************
. *** Table 2: Ordered logit estimates of national economic evaluations using media mentions (W10) and economic similarity (W14) W specifications: lagging state-level conditions
. *************************************************************************************
. foreach W in 10 14 {c -(}
{txt}  2{com}.         di _newline(2) "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  3{com}.         di "W`W'"
{txt}  4{com}.         ologit retnat age male nonwhite union college married unemployed own_home ppid noppid approve inflation ch_unem gsp_pc2_ch_tm1 sp_W`W'_gsp_pc2_ch_tm1
{txt}  5{com}.         estat ic
{txt}  6{com}. 
.         di "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"
{txt}  7{com}. {c )-}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W10

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-206003.53}  
Iteration 1:{space 3}log likelihood = {res:-160785.85}  
Iteration 2:{space 3}log likelihood = {res:-159097.65}  
Iteration 3:{space 3}log likelihood = {res: -159089.7}  
Iteration 4:{space 3}log likelihood = {res:-159089.69}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    203808
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  93827.67
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-159089.69{txt}{col 51}Pseudo R2{col 67}= {res}    0.2277

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .0064151{col 26}{space 2} .0003426{col 37}{space 1}   18.73{col 46}{space 3}0.000{col 54}{space 4} .0057437{col 67}{space 3} .0070866
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.3248133{col 26}{space 2} .0099019{col 37}{space 1}  -32.80{col 46}{space 3}0.000{col 54}{space 4}-.3442206{col 67}{space 3}-.3054061
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2} .0614469{col 26}{space 2} .0118238{col 37}{space 1}    5.20{col 46}{space 3}0.000{col 54}{space 4} .0382726{col 67}{space 3} .0846212
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0479341{col 26}{space 2} .0134931{col 37}{space 1}    3.55{col 46}{space 3}0.000{col 54}{space 4} .0214881{col 67}{space 3} .0743801
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.1961886{col 26}{space 2}  .010363{col 37}{space 1}  -18.93{col 46}{space 3}0.000{col 54}{space 4}-.2164998{col 67}{space 3}-.1758774
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0385077{col 26}{space 2} .0107181{col 37}{space 1}   -3.59{col 46}{space 3}0.000{col 54}{space 4}-.0595147{col 67}{space 3}-.0175007
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .4865471{col 26}{space 2} .0194206{col 37}{space 1}   25.05{col 46}{space 3}0.000{col 54}{space 4} .4484834{col 67}{space 3} .5246107
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1777151{col 26}{space 2} .0120915{col 37}{space 1}  -14.70{col 46}{space 3}0.000{col 54}{space 4}-.2014139{col 67}{space 3}-.1540163
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.6380055{col 26}{space 2} .0160432{col 37}{space 1}  -39.77{col 46}{space 3}0.000{col 54}{space 4}-.6694497{col 67}{space 3}-.6065614
{txt}{space 6}noppid {c |}{col 14}{res}{space 2}  .259262{col 26}{space 2} .0163488{col 37}{space 1}   15.86{col 46}{space 3}0.000{col 54}{space 4}  .227219{col 67}{space 3}  .291305
{txt}{space 5}approve {c |}{col 14}{res}{space 2} -1.81895{col 26}{space 2} .0144029{col 37}{space 1} -126.29{col 46}{space 3}0.000{col 54}{space 4}-1.847179{col 67}{space 3} -1.79072
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} 1.085901{col 26}{space 2} .0071146{col 37}{space 1}  152.63{col 46}{space 3}0.000{col 54}{space 4} 1.071956{col 67}{space 3} 1.099845
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2} .4623788{col 26}{space 2}  .005288{col 37}{space 1}   87.44{col 46}{space 3}0.000{col 54}{space 4} .4520145{col 67}{space 3} .4727431
{txt}gsp_pc2_ch~1 {c |}{col 14}{res}{space 2}-.0038646{col 26}{space 2} .0021739{col 37}{space 1}   -1.78{col 46}{space 3}0.075{col 54}{space 4}-.0081254{col 67}{space 3} .0003962
{txt}sp_W10_gsp~1 {c |}{col 14}{res}{space 2}-.1864589{col 26}{space 2} .0028658{col 37}{space 1}  -65.06{col 46}{space 3}0.000{col 54}{space 4}-.1920758{col 67}{space 3}-.1808421
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-.3466349{col 26}{space 2} .0270562{col 54}{space 4}-.3996641{col 67}{space 3}-.2936056
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} 1.119851{col 26}{space 2} .0270938{col 54}{space 4} 1.066748{col 67}{space 3} 1.172953
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17}203808{col 25}-206003.5{col 37}-159089.7{col 48}   17{col 57} 318213.4{col 69} 318387.2
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
W14

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-206003.53}  
Iteration 1:{space 3}log likelihood = {res:-161214.49}  
Iteration 2:{space 3}log likelihood = {res: -159580.8}  
Iteration 3:{space 3}log likelihood = {res: -159572.9}  
Iteration 4:{space 3}log likelihood = {res: -159572.9}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}    203808
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}  92861.26
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -159572.9{txt}{col 51}Pseudo R2{col 67}= {res}    0.2254

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      retnat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .0065396{col 26}{space 2} .0003421{col 37}{space 1}   19.11{col 46}{space 3}0.000{col 54}{space 4} .0058691{col 67}{space 3} .0072102
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.3250291{col 26}{space 2} .0098896{col 37}{space 1}  -32.87{col 46}{space 3}0.000{col 54}{space 4}-.3444123{col 67}{space 3}-.3056459
{txt}{space 4}nonwhite {c |}{col 14}{res}{space 2}  .066748{col 26}{space 2} .0118213{col 37}{space 1}    5.65{col 46}{space 3}0.000{col 54}{space 4} .0435788{col 67}{space 3} .0899173
{txt}{space 7}union {c |}{col 14}{res}{space 2} .0523745{col 26}{space 2} .0134779{col 37}{space 1}    3.89{col 46}{space 3}0.000{col 54}{space 4} .0259583{col 67}{space 3} .0787907
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.1896216{col 26}{space 2} .0103494{col 37}{space 1}  -18.32{col 46}{space 3}0.000{col 54}{space 4} -.209906{col 67}{space 3}-.1693372
{txt}{space 5}married {c |}{col 14}{res}{space 2}-.0391736{col 26}{space 2} .0107064{col 37}{space 1}   -3.66{col 46}{space 3}0.000{col 54}{space 4}-.0601578{col 67}{space 3}-.0181893
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .4930292{col 26}{space 2} .0193897{col 37}{space 1}   25.43{col 46}{space 3}0.000{col 54}{space 4} .4550261{col 67}{space 3} .5310324
{txt}{space 4}own_home {c |}{col 14}{res}{space 2}-.1816285{col 26}{space 2} .0120789{col 37}{space 1}  -15.04{col 46}{space 3}0.000{col 54}{space 4}-.2053027{col 67}{space 3}-.1579542
{txt}{space 8}ppid {c |}{col 14}{res}{space 2}-.6355696{col 26}{space 2} .0160186{col 37}{space 1}  -39.68{col 46}{space 3}0.000{col 54}{space 4}-.6669654{col 67}{space 3}-.6041738
{txt}{space 6}noppid {c |}{col 14}{res}{space 2} .2565761{col 26}{space 2} .0163309{col 37}{space 1}   15.71{col 46}{space 3}0.000{col 54}{space 4} .2245681{col 67}{space 3} .2885842
{txt}{space 5}approve {c |}{col 14}{res}{space 2}-1.811332{col 26}{space 2} .0143682{col 37}{space 1} -126.07{col 46}{space 3}0.000{col 54}{space 4}-1.839493{col 67}{space 3}-1.783171
{txt}{space 3}inflation {c |}{col 14}{res}{space 2} 1.032809{col 26}{space 2} .0068769{col 37}{space 1}  150.18{col 46}{space 3}0.000{col 54}{space 4} 1.019331{col 67}{space 3} 1.046288
{txt}{space 5}ch_unem {c |}{col 14}{res}{space 2} .4345776{col 26}{space 2} .0052687{col 37}{space 1}   82.48{col 46}{space 3}0.000{col 54}{space 4}  .424251{col 67}{space 3} .4449041
{txt}gsp_pc2_ch~1 {c |}{col 14}{res}{space 2}-.0136318{col 26}{space 2} .0022084{col 37}{space 1}   -6.17{col 46}{space 3}0.000{col 54}{space 4}-.0179601{col 67}{space 3}-.0093035
{txt}sp_W14_gsp~1 {c |}{col 14}{res}{space 2}-.1826254{col 26}{space 2} .0031833{col 37}{space 1}  -57.37{col 46}{space 3}0.000{col 54}{space 4}-.1888646{col 67}{space 3}-.1763862
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-.4876614{col 26}{space 2}  .026916{col 54}{space 4}-.5404158{col 67}{space 3}-.4349069
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} .9718751{col 26}{space 2}  .026904{col 54}{space 4} .9191442{col 67}{space 3} 1.024606
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 13}{c TT}{hline 63}
       Model {c |}    Obs    ll(null)   ll(model)     df          AIC         BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 17}203808{col 25}-206003.5{col 37}-159572.9{col 48}   17{col 57} 319179.8{col 69} 319353.6
{txt}{hline 13}{c BT}{hline 63}
{p 15 22 2}
Note:  N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}
{p_end}
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